DE optimized IPIDF controller for management frequency in a networked power system with SMES and HVDC link
A major concern is frequency change with load. So, Load Frequency Control (LFC) of an interconnected power system is proposed in this research using a unique integral plus proportional integral derivative controller with filter (IPIDF). The Differential Evolution (DE) algorithm is used to optimize t...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Energy Research |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2022.1102898/full |
| _version_ | 1797978560348028928 |
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| author | Ashutosh Biswal Prakash Dwivedi Sourav Bose |
| author_facet | Ashutosh Biswal Prakash Dwivedi Sourav Bose |
| author_sort | Ashutosh Biswal |
| collection | DOAJ |
| description | A major concern is frequency change with load. So, Load Frequency Control (LFC) of an interconnected power system is proposed in this research using a unique integral plus proportional integral derivative controller with filter (IPIDF). The Differential Evolution (DE) algorithm is used to optimize the integral plus proportional integral derivative controller with filter controller parameters for a two-area power system. By contrasting the results of the proposed method with those of recently published optimization techniques for the same power system, such as the Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Firefly Algorithm (FA), and Differential Evolution (DE) based Proportional integral derivative (PID) and PIDF controllers, the superiority of the integral plus proportional integral derivative controller with filter approach is made clear. It is possible to determine the system performance index like integral time multiplied the absolute error (ITAE) and the settling time (Ts). The power system with superconducting magnetic energy storage and an HVDC link is also included in the proposed work, and the values of the suggested integral plus proportional integral derivative controller with filter controllers are evaluated using the Differential Evolution method. By comparing the outcomes with the Differential Evolution tuned PIDF controller for the identical power systems, the suggested controller’s superiority is demonstrated. To show the stability of the recommended Differential Evolution algorithm tuned integral plus proportional integral derivative controller with filter controller, the speed governor, turbine, synchronizing coefficient, and frequency bias parameters’ time constants and operating load conditions are varied in the range of +25 to −25% from their nominal values, along with the magnitude and location of step load perturbation and pulse load perturbation, to perform sensitivity analysis. According to research, proposed integral plus proportional integral derivative controller with filter controllers offer greater dynamic response by minimizing time required to settle and undershoots than Proportional integral derivative controllers and PIDF controllers. MATLAB/Simulink is used to run the simulations. |
| first_indexed | 2024-04-11T05:24:54Z |
| format | Article |
| id | doaj.art-60ba24cabe2742e3b6805917f54f3228 |
| institution | Directory Open Access Journal |
| issn | 2296-598X |
| language | English |
| last_indexed | 2024-04-11T05:24:54Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj.art-60ba24cabe2742e3b6805917f54f32282022-12-23T07:44:46ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2022-12-011010.3389/fenrg.2022.11028981102898DE optimized IPIDF controller for management frequency in a networked power system with SMES and HVDC linkAshutosh BiswalPrakash DwivediSourav BoseA major concern is frequency change with load. So, Load Frequency Control (LFC) of an interconnected power system is proposed in this research using a unique integral plus proportional integral derivative controller with filter (IPIDF). The Differential Evolution (DE) algorithm is used to optimize the integral plus proportional integral derivative controller with filter controller parameters for a two-area power system. By contrasting the results of the proposed method with those of recently published optimization techniques for the same power system, such as the Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Firefly Algorithm (FA), and Differential Evolution (DE) based Proportional integral derivative (PID) and PIDF controllers, the superiority of the integral plus proportional integral derivative controller with filter approach is made clear. It is possible to determine the system performance index like integral time multiplied the absolute error (ITAE) and the settling time (Ts). The power system with superconducting magnetic energy storage and an HVDC link is also included in the proposed work, and the values of the suggested integral plus proportional integral derivative controller with filter controllers are evaluated using the Differential Evolution method. By comparing the outcomes with the Differential Evolution tuned PIDF controller for the identical power systems, the suggested controller’s superiority is demonstrated. To show the stability of the recommended Differential Evolution algorithm tuned integral plus proportional integral derivative controller with filter controller, the speed governor, turbine, synchronizing coefficient, and frequency bias parameters’ time constants and operating load conditions are varied in the range of +25 to −25% from their nominal values, along with the magnitude and location of step load perturbation and pulse load perturbation, to perform sensitivity analysis. According to research, proposed integral plus proportional integral derivative controller with filter controllers offer greater dynamic response by minimizing time required to settle and undershoots than Proportional integral derivative controllers and PIDF controllers. MATLAB/Simulink is used to run the simulations.https://www.frontiersin.org/articles/10.3389/fenrg.2022.1102898/fullload frequency control (LFC)differential evolution (DE) algorithmproportional integral derivative (PID)integral plus proportional integral derivative controller with filter (IPIDF)superconducting magnetic energy storage system (SMES) |
| spellingShingle | Ashutosh Biswal Prakash Dwivedi Sourav Bose DE optimized IPIDF controller for management frequency in a networked power system with SMES and HVDC link Frontiers in Energy Research load frequency control (LFC) differential evolution (DE) algorithm proportional integral derivative (PID) integral plus proportional integral derivative controller with filter (IPIDF) superconducting magnetic energy storage system (SMES) |
| title | DE optimized IPIDF controller for management frequency in a networked power system with SMES and HVDC link |
| title_full | DE optimized IPIDF controller for management frequency in a networked power system with SMES and HVDC link |
| title_fullStr | DE optimized IPIDF controller for management frequency in a networked power system with SMES and HVDC link |
| title_full_unstemmed | DE optimized IPIDF controller for management frequency in a networked power system with SMES and HVDC link |
| title_short | DE optimized IPIDF controller for management frequency in a networked power system with SMES and HVDC link |
| title_sort | de optimized ipidf controller for management frequency in a networked power system with smes and hvdc link |
| topic | load frequency control (LFC) differential evolution (DE) algorithm proportional integral derivative (PID) integral plus proportional integral derivative controller with filter (IPIDF) superconducting magnetic energy storage system (SMES) |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2022.1102898/full |
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